The purpose of this core is to perform image-quality measurements, optimization and quality control for all modalities used in the Program Project, and provide image-processing support. The core is organized into 5 subcores corresponding to the 4-modalities being used and image processing. Additionally the support activities include image data collection, data analysis, software development, dose characterization and safety. (1) The image processing and analysis sub-core will develop algorithms for measuring total glandularity, and for registration of image data from different modalities. (2) The ultrasound sub-core will provide support for quantitative measurements of vascularity and gray scale characteristics of breast lesions. (3) The digital mammography sub-core will maintain the digital mammography system. (4) The magnetic resonance imaging sub- core will maintaining the equipment and manage data flow for the studies performed under the three clinical projects. The MRI sub-core will also maintain custom coil imaging technology, oversee data analysis for time course kinetics, and perform analysis of MR spectra, (5) The PET sub- core will develop and implement the dedicated breast imager (the positron emission tomography service center maintains the PET systems and thus no funding in necessary for QC and other support activities). Attention to these necessary details will allow the PIs to focus on the science. Additionally, the members of the Technology core will be available for consultations with all PIs, to solve clinical problems and get feedback on image quality.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
1P01CA085424-01A2
Application #
6507791
Study Section
Subcommittee E - Prevention &Control (NCI)
Project Start
2001-09-17
Project End
2006-08-31
Budget Start
Budget End
Support Year
1
Fiscal Year
2001
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Type
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Wu, Shandong; Weinstein, Susan; Kontos, Despina (2012) Atlas-based probabilistic fibroglandular tissue segmentation in breast MRI. Med Image Comput Comput Assist Interv 15:437-45
Kontos, Despina; Ikejimba, Lynda C; Bakic, Predrag R et al. (2011) Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment. Radiology 261:80-91
Mavi, Ayse; Cermik, Tevfik F; Urhan, Muammer et al. (2010) The effect of age, menopausal state, and breast density on (18)F-FDG uptake in normal glandular breast tissue. J Nucl Med 51:347-52
Tchou, Julia; Sonnad, Seema S; Bergey, Meredith R et al. (2010) Degree of tumor FDG uptake correlates with proliferation index in triple negative breast cancer. Mol Imaging Biol 12:657-62
Megalooikonomou, Vasileios; Barnathan, Michael; Kontos, Despina et al. (2009) A representation and classification scheme for tree-like structures in medical images: analyzing the branching pattern of ductal trees in X-ray galactograms. IEEE Trans Med Imaging 28:487-93
Bakic, Predrag R; Carton, Ann-Katherine; Kontos, Despina et al. (2009) Breast percent density: estimation on digital mammograms and central tomosynthesis projections. Radiology 252:40-9
Weinstein, Susan P; Localio, A Russell; Conant, Emily F et al. (2009) Multimodality screening of high-risk women: a prospective cohort study. J Clin Oncol 27:6124-8
Kontos, Despina; Bakic, Predrag R; Carton, Ann-Katherine et al. (2009) Parenchymal texture analysis in digital breast tomosynthesis for breast cancer risk estimation: a preliminary study. Acad Radiol 16:283-98
Konecky, Soren D; Choe, Regine; Corlu, Alper et al. (2008) Comparison of diffuse optical tomography of human breast with whole-body and breast-only positron emission tomography. Med Phys 35:446-55
Chen, Sara C; Carton, Ann-Katherine; Albert, Michael et al. (2007) Initial clinical experience with contrast-enhanced digital breast tomosynthesis. Acad Radiol 14:229-38

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